The Impact of Artificial Intelligence on Employment Structures: Mechanisms, Evidence, and Polarization

This study conducts a systematic literature review to examine how artificial intelligence (AI) is reshaping employment structures across sectors. Based on peer-reviewed publications, the analysis identifies four core mechanisms: efficiency enhancement and augmentation, changes in skill requirements, work process transformation, and job creation and replacement. The findings show that AI is particularly effective in automating repetitive and standardized tasks, which not only improves productivity but also lowers entry barriers for some roles while reinforcing the indispensability of advanced expertise in highly specialized domains. At the same time, the integration of AI is driving the reorganization of workflows, with human labor shifting from the role of executor to that of supervisor, coordinator, and creator. These dynamics ultimately manifest in both job substitution and job creation: low-skill and standardized occupations are more vulnerable to automation, while new professions are emerging and traditional roles are being redefined under AI integration. By synthesizing these findings into a mechanism-oriented framework, this review highlights the multifaceted and heterogeneous impacts of AI, showing how efficiency, skills, workflows, and job outcomes are interconnected, and contributing to a clearer understanding of labor market polarization.